Using latent growth curve modeling in clinical treatment research: An example comparing guided self-change and cognitive behavioral therapy treatments for bulimia nervosa1

This experimental study demonstrates the usefulness of multi-group piece-wise latent growth curve models (LGCM) in clinical research, particularly for assessing and comparing treatment effects. Sixty-two female patients (M age = 28.1; SD = 8.00) with bulimia nervosa were randomly assigned to a) a guided self-change treatment (GSC) involving a self-care manual plus 8 bi-weekly sessions of cognitive behavioral therapy or b) 16 weekly sessions of cognitive behavioral therapy (CBT). Both groups showed significant improvements in treatment outcomes during treatment, although CBT showed greater improvements. However, GSC evidenced more continued 1 We are grateful to the British Council (ARC Projekt 269), the German Academic Exchange Service (DAAD, Grant no. Az. 313-ARC-V) and Bielefeld Polytechnic who sponsored the original trial. Therapies were carried out by Barbara Brokbals, Anne Luetzenkirchen, and Hildegard Doil. Diagnostic interviews by these same women and the second author. Rolf Garthe, who analyzed the data for the original study, made them accessible to the first author. Sam Hardy was supported by an institutional training grant (T32 AG20500-01) awarded to John R. Nesselroade by the National Institute on Aging. The first author is grateful for colleagues at the Center on Developmental and Health Research Methodology at the University of Virginia for their statistical consultation, and particularly to John Nesselroade for his mentorship, and to Ryne Estabrook, Denis Gerstorf, Kevin Grimm, Lijuan Wang, and Zhiyong Zhang for their comments on an earlier draft. 2 Correspondence: Departament of Psychology. Brigham Young University. 84602 Provo, UT (USA). E-mail: [email protected]